Big Data in the Age of AI

Description

In this course, you will learn :

• Artificial intelligence (AI), machine learning, and data science all rely on big data, or data that cannot be easily stored or analysed using traditional methods due to its velocity, volume, or variety.
• investigates big data, explaining how it works and shapes our modern data universe
• explains the relationship of big data to AI, data science, social media, and the Internet of Things (IoT).
• discusses some of the ethical issues surrounding the use of big data
• includes techniques for analysing big data, such as data mining and predictive analytics

Syllabus :

1. Defining Big Data

• The volume, velocity, and variety of big data
• Artificial intelligence and machine learning
• Social media and the Internet of Things
• Data warehouses, data lakes, and the cloud
• Edge computing and fog computing

 

2. How Is Big Data Used?

• Big data for business strategy
• Big data for customer interactions
• Big data for applications

 

3. Big Data and Data Science

• Ten ways big data is different from small data
• The three facets of data science
• Data science without big data
• Big data without data science

 

4. Ethics in Big Data

• Big data and privacy
• Data governance

 

5. Data Logistics

• Structured, semi-structured, and unstructured data
• Batch processing vs. stream processing
• Distributed storage and processing
• An evolving data landscape

 

6. Analyzing Big Data

• Challenges with data preparation
• Visualizing big data
• Data mining
• Text analytics
• Sentiment analysis
• Predictive analytics
• Anomaly detection

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